Laetitia Chapel

According to our database, Laetitia Chapel authored at least 38 papers between 2007 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Hyperbolic prototypical network for few shot remote sensing scene classification.

Manal Hamzaoui, Laetitia Chapel, Minh-Tan Pham, Sébastien Lefèvre

Pattern Recognit. Lett., January, 2024

2023

Scalable clustering of segmented trajectories within a continuous time framework: application to maritime traffic data.

Pierre Gloaguen, Laetitia Chapel, Chloé Friguet, Romain Tavenard

Mach. Learn., June, 2023

Fast Optimal Transport through Sliced Wasserstein Generalized Geodesics.

Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty

CoRR, 2023

Hyperbolic Sliced-Wasserstein via Geodesic and Horospherical Projections.

Clément Bonet, Laetitia Chapel, Lucas Drumetz, Nicolas Courty

Proceedings of the Topological, 2023

Match-And-Deform: Time Series Domain Adaptation Through Optimal Transport and Temporal Alignment.

François Painblanc, Laetitia Chapel, Nicolas Courty, Chloé Friguet, Charlotte Pelletier, Romain Tavenard

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Fast Optimal Transport through Sliced Generalized Wasserstein Geodesics.

Guillaume Mahey, Laetitia Chapel, Gilles Gasso, Clément Bonet, Nicolas Courty

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Hyperbolic Variational Auto-Encoder for Remote Sensing Scene Embeddings.

Manal Hamzaoui, Laetitia Chapel, Minh-Tan Pham, Sébastien Lefèvre

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

2022

Time Series Alignment with Global Invariances.

Titouan Vayer, Romain Tavenard, Laetitia Chapel, Rémi Flamary, Nicolas Courty, Yann Soullard

Trans. Mach. Learn. Res., 2022

A Hierarchical Prototypical Network for Few-Shot Remote Sensing Scene Classification.

Manal Hamzaoui, Laetitia Chapel, Minh-Tan Pham, Sébastien Lefèvre

Proceedings of the Pattern Recognition and Artificial Intelligence, 2022

Machine learning for structured data. (Apprentissage machine pour données structurées).

Laetitia Chapel

, 2022

2021

POT: Python Optimal Transport.

Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T. H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

J. Mach. Learn. Res., 2021

Unbalanced Optimal Transport through Non-negative Penalized Linear Regression.

Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning.

Laetitia Chapel, Mokhtar Z. Alaya, Gilles Gasso

CoRR, 2020

Fused Gromov-Wasserstein Distance for Structured Objects.

Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty

Algorithms, 2020

Partial Optimal Tranport with applications on Positive-Unlabeled Learning.

Laetitia Chapel, Mokhtar Z. Alaya, Gilles Gasso

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Sliced Gromov-Wasserstein.

Titouan Vayer, Rémi Flamary, Nicolas Courty, Romain Tavenard, Laetitia Chapel

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optimal Transport for structured data with application on graphs.

Titouan Vayer, Nicolas Courty, Romain Tavenard, Laetitia Chapel, Rémi Flamary

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties.

Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty

CoRR, 2018

Optimal Transport for structured data.

Titouan Vayer, Laetitia Chapel, Rémi Flamary, Romain Tavenard, Nicolas Courty

CoRR, 2018

2017

Scalable Bag of Subpaths Kernel for Learning on Hierarchical Image Representations and Multi-Source Remote Sensing Data Classification.

Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre

Remote. Sens., 2017

Nonlinear Time-Series Adaptation for Land Cover Classification.

Adeline Bailly, Laetitia Chapel, Romain Tavenard, Gustau Camps-Valls

IEEE Geosci. Remote. Sens. Lett., 2017

Efficient Temporal Kernels Between Feature Sets for Time Series Classification.

Romain Tavenard, Simon Malinowski, Laetitia Chapel, Adeline Bailly, Heider Sanchez, Benjamin Bustos

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2017

2016

Combining multiple resolutions into hierarchical representations for kernel-based image classification.

Yanwei Cui, Sébastien Lefèvre, Laetitia Chapel, Anne Puissant

CoRR, 2016

Combining multiscale features for classification of hyperspectral images: A sequence-based kernel approach.

Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre

Proceedings of the 8th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2016

Classification of MODIS time series with Dense Bag-of-Temporal-SIFT-Words: Application to cropland mapping in the Brazilian Amazon.

Adeline Bailly, Damien Arvor, Laetitia Chapel, Romain Tavenard

Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016

2015

Bag-of-Temporal-SIFT-Words for Time Series Classification.

Adeline Bailly, Simon Malinowski, Romain Tavenard, Thomas Guyet, Lætitia Chapel

Proceedings of the 1st International Workshop on Advanced Analytics and Learning on Temporal Data, 2015

Dense Bag-of-Temporal-SIFT-Words for Time Series Classification.

Adeline Bailly, Simon Malinowski, Romain Tavenard, Laetitia Chapel, Thomas Guyet

Proceedings of the Advanced Analysis and Learning on Temporal Data, 2015

A Subpath Kernel for Learning Hierarchical Image Representations.

Yanwei Cui, Laetitia Chapel, Sébastien Lefèvre

Proceedings of the Graph-Based Representations in Pattern Recognition, 2015

2014

PerTurbo Manifold Learning Algorithm for Weakly Labeled Hyperspectral Image Classification.

Laetitia Chapel, Thomas Burger, Nicolas Courty, Sébastien Lefèvre

IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

Hyperspectral image classification from multiscale description with constrained connectivity and metric learning.

Sébastien Lefèvre, Laetitia Chapel, François Merciol

Proceedings of the 6th Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, 2014

Anomaly Detection with Score Functions Based on the Reconstruction Error of the Kernel PCA.

Laetitia Chapel, Chloé Friguet

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

2012

Classwise hyperspectral image classification with PerTurbo method.

Laetitia Chapel, Thomas Burger, Nicolas Courty, Sébastien Lefèvre

Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012

2011

A semantic monitoring and management framework for end-to-end services.

John Keeney, Owen Conlan, Viliam Holub, Miao Wang, Laetitia Chapel, Martin Serrano, Sven van der Meer

Proceedings of the 12th IFIP/IEEE International Symposium on Integrated Network Management, 2011

Inner and Outer Capture Basin Approximation with Support Vector Machines.

Laetitia Chapel, Guillaume Deffuant

Proceedings of the ICINCO 2011 - Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics, Volume 1, Noordwijkerhout, The Netherlands, 28, 2011

2010

Probabilistic approaches to cheating detection in online games.

Laetitia Chapel, Dmitri Botvich, David Malone

Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, 2010

Sparse input matrix and state estimation for linear systems.

Laetitia Chapel, Douglas J. Leith

Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2007

Maintenir la viabilité ou la résilience d'un système : les machines à vecteurs de support pour rompre la malédiction de la dimensionnalité ?

Laëtitia Chapel

PhD thesis, 2007

Approximating Viability Kernels With Support Vector Machines.

Guillaume Deffuant, Laetitia Chapel, Sophie Martin

IEEE Trans. Autom. Control., 2007